We were doing a CRM workshop at a company.
While explaining the data part of the job, I wrote on the board
Then I asked “What information would you like to learn from your target audience?”.
Regardless of the industry, there are almost always the same answers. They also repeated the list below.
- Name and surname
- Date of birth (or Age)
- Gender
- Marital status
- Education (must actually be the School He Finished From)
- Job
- Address
I wrote what was said on the board under Data.
Then I asked what the company expected from this work.
The answers were:
- Which product groups sell better to whom?
- Who are my most frequent customers and what do they buy?
- Who are the customers most likely to respond to the offer offered?
- Which customers are we likely to lose?
- How often and how should we approach which customers?
and this kind of sentences…
I am not writing in more detail so that it is not clear which company it is.
This time, I wrote what was said under Needs.
Then, the image on the board was:
– Let’s talk about how to use the data you mentioned to meet these needs. ” I said. “Does it interest you if someone has a PhD from the USA on advanced financing techniques?“
– No!” they said.
– Does it matter if he is awarded as “the best driver of the city” since the last 3 years?” I asked.
– No!” they said.
Apart from the main business subject of the company, I gave a few more examples of education and professions. All had the same answer: “No!“
– So it is not important for you to “know their profession”. “
I was finally able to get a “Yes” answer.
– Its address is also important as you focus on Anatolia as a company. But only at the city and district level… ”
– Yeah!” they said.
– Now let’s take a look at the data list we just wrote with this perspective. Let’s ask ourselves again the data required to meet our needs. “
After this beginning, we’ve created a more useful (and out of the box) data basket.
We took a break during the workshop. “We’ve never looked this way. We’ve been wondering what to do with the massive data mountain” they said, “We can determine our target more easily now.“
😉
I have written many times. There are companies that have a lot of data and cannot use them (such as banks, GSM, supermarkets). However, it does not start with data, it starts with need.
Need → Information → Information (info) → Data
No wind (data) will help those who do not know where to go (need).
